Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets
A novel clustering algorithm by fast search and find of density peaks (DP) was proposed in Science, 2014. It has attracted much attention from researchers. It can easily select clusters centers with decision graph. However, it cannot be used to cluster manifold data sets as the existing distance mea...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8877709/ |
| _version_ | 1811212085042872320 |
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| author | Dongdong Cheng Jinlong Huang Sulan Zhang Huijun Liu |
| author_facet | Dongdong Cheng Jinlong Huang Sulan Zhang Huijun Liu |
| author_sort | Dongdong Cheng |
| collection | DOAJ |
| description | A novel clustering algorithm by fast search and find of density peaks (DP) was proposed in Science, 2014. It has attracted much attention from researchers. It can easily select clusters centers with decision graph. However, it cannot be used to cluster manifold data sets as the existing distance measurement is not suitable to evaluate the dissimilarity between objects on manifold structure. Some researchers use graph-based distance to measure the dissimilarity between objects on manifold clusters, but computing the graph-based distance on the original data set is time consuming. An improved density peaks clustering algorithm based on shared-neighbors between local cores, SLORE-DP, is proposed in this paper. First, it finds local cores to represent the data set and redefines the graph-based distance between local cores with shared-neighbors-based distance. Then natural neighbor-based density and the new defined graph-based distance are used to construct decision graph on local cores and DP algorithm is employed to cluster local cores. Finally, the remaining points are assigned to the same cluster as their local cores belong to. Since we use the new defined graph-based distance to estimate the dissimilarity between local cores, SLORE-DP can be used to cluster manifold data sets and at the same time it only calculates the shortest path between local cores, which greatly reduces the running time of the algorithm. We do experiments on several synthetic data sets containing manifold clusters and several real data sets from UCI. The results show that SLORE-DP is more effective and efficient than other algorithms when clustering manifold data sets. |
| first_indexed | 2024-04-12T05:24:08Z |
| format | Article |
| id | doaj.art-f231b8e4f47547808bbafe9b8a112bc5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T05:24:08Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f231b8e4f47547808bbafe9b8a112bc52022-12-22T03:46:22ZengIEEEIEEE Access2169-35362019-01-01715133915134910.1109/ACCESS.2019.29484228877709Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data SetsDongdong Cheng0https://orcid.org/0000-0003-3500-5461Jinlong Huang1Sulan Zhang2https://orcid.org/0000-0003-1092-375XHuijun Liu3College of Big Data and Intelligent Engineering, Yangtze Normal University, Chongqing, ChinaCollege of Big Data and Intelligent Engineering, Yangtze Normal University, Chongqing, ChinaCollege of Big Data and Intelligent Engineering, Yangtze Normal University, Chongqing, ChinaCollege of Computer Science, Chongqing University, Chongqing, ChinaA novel clustering algorithm by fast search and find of density peaks (DP) was proposed in Science, 2014. It has attracted much attention from researchers. It can easily select clusters centers with decision graph. However, it cannot be used to cluster manifold data sets as the existing distance measurement is not suitable to evaluate the dissimilarity between objects on manifold structure. Some researchers use graph-based distance to measure the dissimilarity between objects on manifold clusters, but computing the graph-based distance on the original data set is time consuming. An improved density peaks clustering algorithm based on shared-neighbors between local cores, SLORE-DP, is proposed in this paper. First, it finds local cores to represent the data set and redefines the graph-based distance between local cores with shared-neighbors-based distance. Then natural neighbor-based density and the new defined graph-based distance are used to construct decision graph on local cores and DP algorithm is employed to cluster local cores. Finally, the remaining points are assigned to the same cluster as their local cores belong to. Since we use the new defined graph-based distance to estimate the dissimilarity between local cores, SLORE-DP can be used to cluster manifold data sets and at the same time it only calculates the shortest path between local cores, which greatly reduces the running time of the algorithm. We do experiments on several synthetic data sets containing manifold clusters and several real data sets from UCI. The results show that SLORE-DP is more effective and efficient than other algorithms when clustering manifold data sets.https://ieeexplore.ieee.org/document/8877709/Shared-neighborslocal coresdensity peaksclustering |
| spellingShingle | Dongdong Cheng Jinlong Huang Sulan Zhang Huijun Liu Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets IEEE Access Shared-neighbors local cores density peaks clustering |
| title | Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets |
| title_full | Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets |
| title_fullStr | Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets |
| title_full_unstemmed | Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets |
| title_short | Improved Density Peaks Clustering Based on Shared-Neighbors of Local Cores for Manifold Data Sets |
| title_sort | improved density peaks clustering based on shared neighbors of local cores for manifold data sets |
| topic | Shared-neighbors local cores density peaks clustering |
| url | https://ieeexplore.ieee.org/document/8877709/ |
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